To cope with the explosive bandwidth demand, significant progress has be...
Current clustering-based Open Relation Extraction (OpenRE) methods usual...
Semantic matching is a mainstream paradigm of zero-shot relation extract...
The existing supervised relation extraction methods have achieved impres...
Prompting methods such as Chain-of-Thought (CoT) have shed new light on
...
Pretrained language models have achieved remarkable success in various
n...
Existing models for named entity recognition (NER) are mainly based on
l...
Models trained with empirical risk minimization (ERM) are revealed to ea...
The principle of continual relation extraction (CRE) involves adapting t...
Large language models have unlocked strong multi-task capabilities from
...
GPT series models, such as GPT-3, CodeX, InstructGPT, ChatGPT, and so on...
The GPT-3.5 models have demonstrated impressive performance in various
N...
Multilingual BERT (mBERT) has demonstrated considerable cross-lingual
sy...
Adversarial training is one of the most powerful methods to improve the
...
Dialogue summarization aims to condense the lengthy dialogue into a conc...
Recent works on Lottery Ticket Hypothesis have shown that pre-trained
la...
As the categories of named entities rapidly increase in real-world
appli...
Datasets with significant proportions of bias present threats for traini...
Despite having achieved great success for sentiment analysis, existing n...
Input distribution shift is one of the vital problems in unsupervised do...
NER model has achieved promising performance on standard NER benchmarks....
Text semantic matching is a fundamental task that has been widely used i...
Plug-and-play functionality allows deep learning models to adapt well to...
Prompt-based methods have been successfully applied in sentence-level
fe...
The clustering-based unsupervised relation discovery method has graduall...
The encoder-decoder framework achieves state-of-the-art results in keyph...
With the rapid increase in the volume of dialogue data from daily life, ...
Distant supervision for relation extraction provides uniform bag labels ...
Named Entity Recognition (NER) is the task of identifying spans that
rep...
Recently, the sequence-to-sequence models have made remarkable progress ...
Various robustness evaluation methodologies from different perspectives ...
Conditional random fields (CRF) for label decoding has become ubiquitous...
Multi-task learning (MTL) has received considerable attention, and numer...
Word representation is a key component in neural-network-based sequence
...
Multi-criteria Chinese word segmentation is a promising but challenging ...
In recent years, long short-term memory (LSTM) has been successfully use...
There is a fundamental limit on the capacity of fibre optical communicat...